Sudip Kumar Naskar

1.7k total citations
139 papers, 1.0k citations indexed

About

Sudip Kumar Naskar is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sudip Kumar Naskar has authored 139 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 113 papers in Artificial Intelligence, 13 papers in Molecular Biology and 13 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sudip Kumar Naskar's work include Natural Language Processing Techniques (89 papers), Topic Modeling (83 papers) and Speech and dialogue systems (14 papers). Sudip Kumar Naskar is often cited by papers focused on Natural Language Processing Techniques (89 papers), Topic Modeling (83 papers) and Speech and dialogue systems (14 papers). Sudip Kumar Naskar collaborates with scholars based in India, Ireland and Germany. Sudip Kumar Naskar's co-authors include Sivaji Bandyopadhyay, Andy Way, Asif Ekbal, Santanu Pal, Josef van Genabith, Somnath Banerjee, Rejwanul Haque, Dipankar Mandal, Paolo Rosso and Mihaela Vela and has published in prestigious journals such as Journal of the American Chemical Society, Advanced Materials and ACS Nano.

In The Last Decade

Sudip Kumar Naskar

124 papers receiving 896 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Sudip Kumar Naskar India	18	825	122	93	61	56	139	1.0k
Partha Pakray India	15	674 0.8×	194 1.6×	100 1.1×	36 0.6×	21 0.4×	120	861
Abdelmajid Ben Hamadou Tunisia	13	481 0.6×	157 1.3×	115 1.2×	82 1.3×	18 0.3×	95	683
Yee Seng Chan Singapore	16	945 1.1×	51 0.4×	66 0.7×	81 1.3×	17 0.3×	23	1.1k
Alexander Clark United Kingdom	17	902 1.1×	62 0.5×	57 0.6×	53 0.9×	125 2.2×	66	1.1k
Manaal Faruqui United States	13	1.4k 1.7×	187 1.5×	87 0.9×	106 1.7×	19 0.3×	46	1.5k
Manfred Pinkal Germany	19	990 1.2×	563 4.6×	81 0.9×	22 0.4×	132 2.4×	58	1.5k
Ahmed El Kholy United States	8	703 0.9×	230 1.9×	82 0.9×	20 0.3×	42 0.8×	23	783
Shinsuke Mori Japan	15	852 1.0×	243 2.0×	93 1.0×	38 0.6×	19 0.3×	107	996
Juan‐Manuel Torres‐Moreno France	13	350 0.4×	37 0.3×	96 1.0×	13 0.2×	23 0.4×	72	505
Kavi Mahesh India	10	230 0.3×	46 0.4×	55 0.6×	21 0.3×	25 0.4×	43	383

Countries citing papers authored by Sudip Kumar Naskar

Since Specialization

Citations

This map shows the geographic impact of Sudip Kumar Naskar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sudip Kumar Naskar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sudip Kumar Naskar more than expected).

Fields of papers citing papers by Sudip Kumar Naskar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sudip Kumar Naskar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sudip Kumar Naskar. The network helps show where Sudip Kumar Naskar may publish in the future.

Co-authorship network of co-authors of Sudip Kumar Naskar

This figure shows the co-authorship network connecting the top 25 collaborators of Sudip Kumar Naskar. A scholar is included among the top collaborators of Sudip Kumar Naskar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sudip Kumar Naskar. Sudip Kumar Naskar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Naskar, Sudip Kumar, Bidya Mondal, Asif Iqbal, et al.. (2025). Acousto‐Electric Conversion by the Piezoelectric Nanogenerator of a Molecular Copper(II) Complex. Advanced Materials. 37(39). e2504086–e2504086. 1 indexed citations

Ganguly, Debasis, et al.. (2025). The “Curious Case of Contexts” in Retrieval‐Augmented Generation With a Combination of Labeled and Unlabeled Data. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 15(2). 1 indexed citations

Roy, Krittish, et al.. (2025). Functionalized Graphene Reinforced Composite Nanofiber Membrane for Efficient Pyroelectric Energy Harvesting and Sensing. Small. 21(37). e05798–e05798.

Ganguly, Debasis, et al.. (2025). HF-RAG: Hierarchical Fusion-based RAG with Multiple Sources and Rankers. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 5202–5207.

Naskar, Sudip Kumar, et al.. (2024). Harnessing thermal waste with a poling-free molecular pyroelectric zinc(ii) complex. Chemical Communications. 61(2). 318–321. 1 indexed citations

Kumar, Ajay, Sudip Kumar Naskar, & Dipankar Mandal. (2023). Single material with multiple interfaces: A key one dimensional barium titanate filler for enhancing energy density in polymer nanocomposite. Surfaces and Interfaces. 38. 102863–102863. 7 indexed citations

Naskar, Sudip Kumar, et al.. (2022). Ranking Environment, Social And Governance Related Concepts And Assessing Sustainability Aspect of Financial Texts. 243–249. 4 indexed citations

Banerjee, Somnath, Sudip Kumar Naskar, Paolo Rosso, & Sivaji Bandyopadhyay. (2018). Code mixed cross script factoid question classification - A deep learning approach. Journal of Intelligent & Fuzzy Systems. 34(5). 2959–2969. 4 indexed citations

Naskar, Sudip Kumar, et al.. (2017). Natural Language Programing with Automatic Code Generation towards Solving Addition-Subtraction Word Problems. 146–154. 1 indexed citations

10.

Ekbal, Asif, et al.. (2016). Biomolecular Event Extraction using a Stacked Generalization based Classifier.. 55–64. 12 indexed citations

11.

Pal, Santanu, Sudip Kumar Naskar, & Josef van Genabith. (2016). Multi-Engine and Multi-Alignment Based Automatic Post-Editing and its Impact on Translation Productivity. International Conference on Computational Linguistics. 2559–2570. 7 indexed citations

12.

Pal, Santanu, et al.. (2016). CATaLog Online: Porting a Post-editing Tool to the Web.. Language Resources and Evaluation. 599–604. 7 indexed citations

13.

Gaspari, Federico, Antonio Toral, Sudip Kumar Naskar, Declan Groves, & Andy Way. (2014). Perception vs. reality: measuring machine translation post-editing productivity. Conference of the Association for Machine Translation in the Americas. 60–72. 21 indexed citations

14.

Pal, Santanu, Sudip Kumar Naskar, & Sivaji Bandyopadhyay. (2013). A Hybrid Word Alignment Model for Phrase-Based Statistical Machine Translation. 94–101. 10 indexed citations

15.

Toral, Antonio, et al.. (2013). A Web Application for the Diagnostic Evaluation of Machine Translation over Specific Linguistic Phenomena. North American Chapter of the Association for Computational Linguistics. 20–23. 1 indexed citations

16.

Banerjee, Pratyush, Sudip Kumar Naskar, Johann Roturier, Andy Way, & Josef van Genabith. (2012). Translation Quality-Based Supplementary Data Selection by Incremental Update of Translation Models. International Conference on Computational Linguistics. 149–166. 8 indexed citations

17.

Pal, Santanu, Sudip Kumar Naskar, Pavel Pecina, Sivaji Bandyopadhyay, & Andy Way. (2010). Handling Named Entities and Compound Verbs in Phrase-Based Statistical Machine Translation. Arrow@dit (Dublin Institute of Technology). 46–54. 19 indexed citations

18.

Somers, Harold, Sandipan Dandapat, & Sudip Kumar Naskar. (2009). A review of EBMT using proportional analogies. Arrow@dit (Dublin Institute of Technology). 5 indexed citations

19.

Haque, Rejwanul, Sudip Kumar Naskar, Josef van Genabith, & Andy Way. (2009). Experiments on Domain Adaptation for English--Hindi SMT. Arrow@dit (Dublin Institute of Technology). 670–677. 8 indexed citations

20.

Haque, Rejwanul, Sudip Kumar Naskar, Antal van den Bosch, & Andy Way. (2009). Dependency Relations as Source Context in Phrase-Based SMT. Research portal (Tilburg University). 1. 170–179. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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